Multi-scale network reconstruction and modelling of phage – bacteria interactions

Bacteriophages are viruses that infect bacteria. They are seen as a promising alternative to antibiotics, particularly as multi-resistant bacterial strains are becoming more widespread and could one day render existing antibiotic therapies ineffective. Nevertheless, our understanding of how phages take control of their bacterial hosts remains very limited. Network analysis and systems biology provide powerful techniques to better understand interactions between viruses and their hosts. The first step generally consists in reconstructing a comprehensive set of protein-protein interactions, which is now becoming possible for phage–bacteria interactions thanks to the rapid growth of experimental datasets.

However, network reconstruction only provides limited insight into the biology of virus–host interactions, since many of these protein-protein interactions are context dependent, occur at different time and spatial scales, and differ in nature. Moreover, there is growing evidence that biological systems are hierarchically organised, but the ‘flat’ nature of network representations fails to take this property into account. New theoretical frameworks are therefore needed to account both for context variations and for the multi-scale nature of biological systems.

The aims of this project are (1) to analyse existing datasets of molecular interactions between phages and their bacterial hosts in order to reconstruct comprehensive network representations of virus–host interactions, and (2) to develop and implement a new context-specific and multi-scale modelling framework based on a concept of ‘organisation’ that renders hierarchy explicit. This project is highly interdisciplinary and suited for theory-minded candidates with a background in mathematics, computer science, physics or biology.

Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area / subject. Candidates with experience in mathematics, computer science, physics or biology are encouraged to apply.